π Ready to supercharge your Python testing? Let’s dive into an engaging tutorial that transforms PyTest from a simple test runner into a powerful, customizable powerhouse! πͺ
π What you’ll learn:
– Set up a project structure for organized testing.
– Configure PyTest with plugins, fixtures, and markers.
– Write tests for custom objects, logic, and side effects.
– Control and run tests with custom options.
– Generate JSON reports for easy integration with CI/CD pipelines.
π» Let’s get started!
1. Set up your environment and project structure:
– Install the latest PyTest and create a clean project folder with `calc`, `app`, and `tests` subfolders.
2. Configure PyTest:
– In `pytest.ini`, define markers, default options, and test paths.
– In `conftest.py`, create a custom plugin that tracks test results, adds a `–runslow` option, and provides fixtures for reusable test resources.
3. Build your core calculation module:
– In the `calc` package, define simple mathematical utilities and a custom `Vector` class for testing.
4. Add app utilities and write tests:
– Create lightweight app utilities for JSON I/O and a mocked API.
– Write focused tests using parametrization, xfail, markers, tmp_path, capsys, and monkeypatch.
5. Run and summarize test results:
– Run the test suite twice: once with the default configuration and once with the `–runslow` flag.
– Generate a JSON summary containing test outcomes, the total number of test files, and a sample event log.
π By the end of this tutorial, you’ll understand not just how to write tests, but how to control and customize PyTest’s behavior to fit any project’s needs. You’ll be ready to extend PyTest further with coverage, benchmarking, or parallel execution for large-scale, professional-grade testing.
π Check out the full codes here and explore our GitHub page for more tutorials, codes, and notebooks. Follow us on Twitter, join our 100k+ ML SubReddit, subscribe to our newsletter, and even join us on Telegram for more tech goodness! π€π
Happy testing! π
